# Copyright 2021 Huawei Technologies Co., Ltd

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

# ============================================================================





"""

Export onnx from ckpt

"""

import hydra

import os

import torch

from deepspeech_pytorch.configs.inference_config import EvalConfig

from deepspeech_pytorch.utils import load_model

import argparse



parser = argparse.ArgumentParser(description='Deepspeech')

parser.add_argument('--ckpt_path', default='./an4_pretrained_v3.ckpt', type=str, help='infer out path')

parser.add_argument('--out_file', default='deepspeech.onnx', type=str, help='infer info path')

args = parser.parse_args()



if __name__ == '__main__':

    device = torch.device("cpu")

    # device = torch.device("cuda" if EvalConfig.model.cuda else "cpu")

    model = load_model(device=device, model_path=args.ckpt_path)

    model.eval()

    model = model.to(device)

    print('Finished loading model!')

    # print(model)

    input_names = ["spect", "transcript"]

    output_names = ["out"]

    dynamic_axes = {'spect': {0: '-1'}}

    dummy_input = torch.randn(1, 1, 161, 621).to(device)

    dummy_input2 = torch.tensor([621], dtype=torch.int32).to(device)

    output_file = args.out_file

    torch.onnx.export(model, [dummy_input, dummy_input2], output_file, 

                      input_names=input_names, dynamic_axes=dynamic_axes, 

                      output_names=output_names, opset_version=11, verbose=True)